R-Ladies chapters from the Netherlands are gathering forces to host online book clubs!
We are very excited to start with the book Advanced R by Hadley Wickham.
Highlight the key points on each topic of the book with a presentation.
Go together through the exercises.
Discuss and clarify doubts.
The events will be hosted every two weeks by different R-Ladies chapters, on Tuesdays at 6pm, via zoom.
| chapter | title | description | speaker | date | hosted_by | link |
|---|---|---|---|---|---|---|
| 2 | Names and values | Teaches you about an important distinction that you probably haven’t thought deeply about: the difference between an object and its name. Improving your mental model here will help you make better predictions about when R copies data and hence which basic operations are cheap and which are expensive | Laurel Brehm | 2020-04-07 | Nijmengen | click here |
| 3 | Vectors | Dives into the details of vectors, helping you learn how the different types of vector fit together. You’ll also learn about attributes, which allow you to store arbitrary metadata, and form the basis for two of R’s object-oriented programming toolkits. | Paloma Rojas | 2020-04-21 | Rotterdam | NA |
| 4 | Subsetting | Describes how to use subsetting to write clear, concise, and efficient R code. Understanding the fundamental components will allow you to solve new problems by combining the building blocks in novel ways. | Martine Jansen | 2020-05-12 | Den Bosch | NA |
| 5 | Control flow | Presents tools of control flow that allow you to only execute code under certain conditions, or to repeatedly execute code with changing inputs. These include the important if and for constructs, as well as related tools like switch() and while. | Margaux Sleckman | 2021-05-26 | Amsterdam | NA |
| 6 | Functions | Deals with functions, the most important building blocks of R code. You’ll learn exactly how they work, including the scoping rules, which govern how R looks up values from names. You’ll also learn more of the details behind lazy evaluation, and how you can control what happens when you exit a function. | Sign up! | NA | NA | NA |
| 7 | Environments | Describes a data structure that is crucial for understanding how R works, but quite unimportant for data analysis: the environment. Environments are the data structure that binds names to values, and they power important tools like package namespaces. Unlike most programming languages, environments in R are “first class†which means that you can manipulate them just like other objects. | Sign up! | NA | NA | NA |
Sign-up to present a topic here
To join the event, click at the link on our Current agenda!
Looking forward to see you soon!